similar to: Memory Limits in Ubuntu Linux

I'm trying to use stepAIC on sparse matrices, and I need some help. The documentation for slm.fit suggests: slm.fit and slm.wfit call slm.fit.csr to do Cholesky decomposition and then backsolve to obtain the least squares estimated coefficients. These functions can be called directly if the user is willing to specify the design matrix in matrix.csr form. This is often advantageous in large

What is the most efficient alternative to x[order(x)][1:n] where length(x)>>n? I also need the positions of the mins/maxs perhaps by preserving names. Thanks for any suggestions. -- View this message in context: http://www.nabble.com/Largest-N-Values-Efficiently--tf4788033.html#a13697535 Sent from the R help mailing list archive at Nabble.com.

Looking for help with a project for the US Navy, requires knowledge of Bayesian Statistics, Bayesian Networks and Survival Analysis. Please respond with CV. Thanks. -- David Katz www.davidkatzconsulting.com [[alternative HTML version deleted]]

I was surprised to see this unexpected behavior of subset in a for loop. I looked in subset.data.frame and it seemed to me that both versions should work, since the subset call should be evaluated in the global environment - but perhaps I don't understand environments well enough. Can someone enlighten me? In any case, this is a bit of a gotcha for naive users of subset. input.data <-

Hi, I have spatially autocorrelated data (with a binary response variable and continuous predictor variables). I believe I need to do an autologistic model, does anyone know a method for doing this in R? Many thanks C Bell

Dear R gurus, first let me apologize for a question that might hve been answered before. I was not able to find the solution yet. I want to concatenate two lists of lists at their lowest level. Suppose I have two lists of lists: list.1 <- list("I"=list("A"=c("a", "b", "c"), "B"=c("d", "e", "f")),

I''m using scriptaculous'' SlideUp and SlideDown effects to animate a menu. Specifically, I SlideUp, make some CSS changes, and SlideDown. All works well, except that for a split second in between, the element''s display becomes ''none'' and the other menu item jump into the space. I haven''t been able to find any way to force an element to retain

I posted the following earlier: "I need a way to do a blind up that makes the element APPEAR and a blind down that makes the element DISAPPEAR. In essence, the opposite of the current blindup/blinddown. Thoughts?" I think somebody responded in Dutch. Anyone else have any ideas? -- Yehuda Katz Web Developer (ph) 718.877.1325 (fax) 718.686.4288

Hi All, I am trying to learn Neural Networks. I found that R has packages which can help build Neural Nets - the popular one being AMORE package. Is there any book / resource available which guides us in this subject using the AMORE package? Any help will be much appreciated. Thanks, Indrajit

Hi everyone, I'm a graduate student of engineering, lately introduced with R. and using R for my project and thesis. I'm trying to use R for implementing a neural network regression model and apply it to my database. I found three R packages ("AMORE" , "grnnR" , "neural") in R website, but their manuals are not really user-friendly in my idea. I was wondering

Hey all, I have released some pre-alpha code for my Administrative Console which I''ve been talking about for the past few days. The admin console, autoDB, provides and AJAXed, automated scaffolding-type system that''s pretty and very customizable. More details at http://trac.visualjquery.com/admin_console/ and my original post from last week, which has screenshots and some

How do I check if the proper sata drivers are being loaded? If they are not what can I do other then rebuilding the kernel? Thank you in advance, Randy _______________________________________________ Xen-users mailing list Xen-users@lists.xensource.com http://lists.xensource.com/xen-users

Hi! I am studying to use some R libraries which are applied for working with artificial neural neworks (amore, nnet). Can you recommend some useful, reliable and easy to get example data to use in R for creating and testing a neural network? __________________________________________________________________ Make your browsing faster, safer, and easier with the new Internet

Hello, when I store a file biger than 2GB to a samba server version 2.2.5 everythink works fine. But when I do that with a server version 2.2.6 or 2.2.7 the saving fails on the 2GB limit. The problem can be seen with windowsclients or with smbclient (any version > 2.2.5). I did some debuging and find that the lseek64 fails. But I didn't find the reason. Regards Klaus Ethgen

Hi. I started with a file which was a sparse 982x923 matrix and where the last column was a variable to be predicted. I did principle component analysis on it and arrived at a new 982x923 matrix. Then I ran the code below to get a neural network using nnet and then wanted to get a confusion matrix or at least know how accurate the neural net was. I used the first 22 principle components only for

I am interested in Neural network models in R. Is there any reference material/tutorial which i can use. Regards, ____________________________________________________________________________________ TV dinner still cooling? Check out "Tonight's Picks" on Yahoo! TV.

If any of you have been so bold as to install the Shorewall CA Certificate in your browser(s), the current certificate will expire on 11/13. There is a new 10-year certificate available for installation at: http://lists.shorewall.net/Shorewall_CA_html.html -Tom -- Tom Eastep \ Nothing is foolproof to a sufficiently talented fool Shoreline, \ http://shorewall.net Washington USA \

Hi all, I am trying to develop a neural network with single target variable and 5 input variables to predict the importance of input variables using R. I used the packages nnet and RSNNS. But unfortunately I could not interpret the out put properly and the documentation of that packages also not giving proper direction. Please help me to find a good package with a proper documentation for neural

Hello, I use nnet to do prediction for a continuous variable. after that, I calculate correlation coefficient between predicted value and real observation. I run my code(see following) several time, but I get different correlation coefficient each time. Anyone know why? In addition, How to calculate prediction accuracy for prediction of continuous variable? Aimin thanks, > m.nn.omega

Mpiktas <mpiktas at delfi.lt> wrote : >Something like memory.limit(512) will do the trick Luis Silva <lm.silva at sapo.pt> wrote : >I had that problem already. In windows I did this >C:\Programas\R\rw1060\bin\Rgui.exe --max-mem-size=400M >in the icon path of R. You'll have to try several sizes. I believe recent versions of R on Windows automatically set